Skill UI

This guide assists users in structuring and rigorously defending the methodological design for demographic manuscripts. It provides detailed guidance on selecting and justifying advanced techniques—including life tables, decomposition analysis, survival models, Age-Period-Cohort (APC) modeling, and microsimulation. It emphasizes critical steps like establishing identification assumptions, addressing causal biases (selection and exposure), and formulating an adjudication test to rule out rival explanations, ensuring the research is methodologically robust.

This skill provides comprehensive guidance for authors submitting manuscripts to Environment International. It focuses on the rigorous connection between measured environmental exposures (including the exposome, contaminants, and mixtures) and quantifiable, population-relevant human health outcomes or risks. It covers methodology requirements, epidemiological rigor, and journal-specific formatting standards to improve manuscript suitability and reduce desk rejection risk.

A comprehensive guide for econometricians submitting manuscripts to top journals. It details how to structure analyses for full reproducibility, including using master scripts, pinning software versions, and exporting results to plain-text formats. Coverage includes advanced robust inference techniques such as HAC, cluster bootstrapping, and weak-IV diagnostics, ensuring the work satisfies rigorous archival standards.

A comprehensive methodology guide for designing rigorous multi-country or cross-cultural studies, essential for international marketing research. It covers critical steps such as country selection criteria, ensuring construct, translation, and sampling equivalence, and planning for measurement invariance (MGCFA). It guides researchers through advanced designs including cross-cultural experiments, multi-level estimation, and handling secondary export/entry-mode data.

This guide provides rigorous structural and stylistic guidelines for academic manuscripts in the field of risk and uncertainty. It instructs authors on how to precisely articulate decision models, quantify results with appropriate magnitude and precision, and structure arguments (Abstract, Introduction, Exposition) to meet the high standards of specialized journals, ensuring technical honesty and clarity.

This guide helps researchers elevate vague global trends into rigorous, open-economy causal questions suitable for high-impact journals. It teaches methodology for identifying clear treatments, measuring international exposure (e.g., GVC, trade dependency), and defining precise counterfactuals within a general equilibrium framework.

A comprehensive framework for designing, auditing, and reporting empirical results in recommender systems research. It covers best practices for handling temporal splits, mitigating evaluation bias (e.g., exposure/popularity), utilizing advanced off-policy estimators (IPS, SNIPS), and structuring the critical link between offline metrics and real-world A/B test results. Essential for academic submissions.

This guide provides a comprehensive strategy for elevating the credibility of finance manuscripts to the standard of top-tier journals. It details rigorous methods for empirical causal identification (DID, IV, RDD, natural experiments) and ensures theoretical rigor by assessing assumptions, generalizability, and proof exposition. It helps researchers stress-test their work's core logic.

This skill facilitates the extraction of population-scale (cohort-level) clinical text from Electronic Health Records (EHR) or FHIR data warehouses using the FHIR Bulk Data Access ($export) operation. It manages the asynchronous job kickoff, polling, and downloading of NDJSON files. The resulting data stream is designed to be fed in batches into OpenMed for mandatory de-identification and Named Entity Recognition (NER) analysis.

This skill parses standardized C-CDA/CCD XML clinical documents exported from EHRs. It extracts both human-readable section narrative text and coded entries, mapping them by LOINC codes and template IDs. It is essential for preparing clinical free-text data for subsequent NLP analysis and supports XML-aware de-identification while preserving document structure.

A powerful command-line interface for interacting with Zotero libraries. It allows users to programmatically search, retrieve, and manipulate academic references, including fetching full text, updating metadata, managing tags, and exporting bibliographies. Ideal for automating research workflows and building data pipelines.

This skill performs pharmacokinetic and pharmacodynamic modelling, including non-compartmental analysis, compartmental fitting, and population PK. It helps derive exposure metrics, evaluate dosing regimens, and predict drug interactions using Python scripts. Suitable for analyzing concentration-time data and supporting clinical pharmacology workflows.